Structured Thinking MCP Server
by Promptly-Technologies-LLC
A TypeScript Model Context Protocol (MCP) server that allows LLMs to programmatically construct mind maps to explore an idea space, with enforced metacognitive self-reflection. It is based on Arben Ademi's Sequential Thinking Python server.
Last updated: N/A
What is Structured Thinking MCP Server?
This server is a TypeScript implementation of a Model Context Protocol (MCP) server designed to enable Large Language Models (LLMs) to create mind maps programmatically. It enforces metacognitive self-reflection by providing feedback to the LLM based on the quality and stage of its thoughts.
How to use Structured Thinking MCP Server?
To use this server, configure your MCP client (e.g., Claude Desktop, Cursor) with the provided JSON configuration. This configuration specifies the command and arguments needed to run the server. The LLM will then interact with the server through MCP tools to capture, revise, and retrieve thoughts, and generate summaries.
Key features of Structured Thinking MCP Server
Thought Quality Scores
Thought Stages
Thought Branching
Memory Management
Use cases of Structured Thinking MCP Server
Idea Exploration
Problem Solving
Knowledge Discovery
Metacognitive Feedback
FAQ from Structured Thinking MCP Server
How does the server provide metacognitive feedback?
How does the server provide metacognitive feedback?
The server uses thought quality scores and thought stages to provide feedback to the LLM, encouraging it to steer its thinking process.
What is the purpose of thought stages?
What is the purpose of thought stages?
Thought stages (e.g., Problem Definition, Analysis, Ideation) help manage the life-cycle of the LLM's thinking process and provide context for metacognitive feedback.
How does the server manage memory?
How does the server manage memory?
The server maintains a short-term memory buffer of the LLM's ten most recent thoughts and a long-term memory of thoughts that can be retrieved based on their tags.
What MCP tools are exposed by the server?
What MCP tools are exposed by the server?
The server exposes tools such as capture_thought, revise_thought, retrieve_relevant_thoughts, get_thinking_summary, and clear_thinking_history.
What are the limitations of the current implementation?
What are the limitations of the current implementation?
The current implementation has naive metacognitive monitoring and lacks a user interface for visualizing the thought space.